I had the opportunity to hear Nuno Costa, Senior Director, Cloud and AI, Microsoft Azure Marketplace during Outsystems' NextStep user conference. While I was not able to speak to Nuno after his presentation on "The AI Transformation," I was able to get the following answers to my questions from Microsoft:

What Are Microsoft's Keys to a Client's Successful AI Strategy?

Microsoft’s goal is to make AI accessible to every organization and help augment human ingenuity through the power of intelligent technology. We do this using a thoughtful approach when designing AI systems that extend and empower human capabilities in all aspects of life.

Leading innovation that extends your capabilities: When we add AI capabilities to products (including mainstream products like Bing Search, PowerPoint and Skype translator) they are often rooted in discoveries from Microsoft’s research labs.

Building powerful platforms that make innovation faster and more accessible: We have created APIs and other tools that developers, customers and data scientists can use to add intelligence into existing products and services or to build new ones.

Developing a trusted approach that puts you in control and protects your data: As AI systems get more sophisticated and start to play a larger role in people’s lives, it’s imperative for companies to develop and adopt clear principles that guide the people building, using and applying AI systems.

We partner with our customers to understand their most pressing business problems and develop solutions that will impact their business. It’s not possible to code enterprise knowledge and experience in a few years. And the reach and experience we can bring are not ours alone — Microsoft has hundreds of thousands of partners lighting up solutions that modern digital businesses need.

What Are the Technical Solutions Azure Is Providing Clients for Their AI Initiatives?

Microsoft is enabling businesses to transform through providing a powerful platform of tools and services that can be infused into solutions. We have created APIs and other tools that developers, customers and data scientists can use to add intelligence into existing products and services or to build new ones.

Some of our technical solutions include:

Azure Cognitive Services is a collection of RESTful intelligent APIs that allow systems to see, hear, speak, understand and interpret our needs using natural methods of communication. Developers can use these APIs to make their applications more intelligent, engaging and discoverable. More than 1.2 million developers from 60 countries are using Azure Cognitive Services to build apps that do things like recognize gestures, convert speech into text or identify, caption and moderate images.

Azure Bot Service provides everything you need as a developer to build and connect intelligent bots that interact naturally wherever your users are talking, from text/SMS to Skype, Slack, Office 365 mail and other popular services. More than 340,000 developers have signed up to use Azure Bot Service to create bots that can interact naturally with customers on websites and in apps.

Deep Learning Tools helpdata scientists and developers build, and train AI models faster and then easily deploy to the cloud or the edge. Significant new updates to Azure Machine Learning include automated machine learning to identify the most efficient algorithms and optimize model performance, additional hardware-accelerated models for FPGAs and a Python SDK that makes Azure Machine Learning services accessible from popular IDEs and notebooks.

All of these tools run on Microsoft’s Azure cloud computing platform, which now spans 36 regions around the world and provides the backbone for many customers who are developing and running AI-infused products and services.

What Are Real-World Problems Your Clients Are Solving With AI?

Microsoft customers are using AI to solve a wide variety of challenges, including:

Global oil and gas company, Shell, is applying AI to maximize the productivity of its drilling equipment and keep its gas stations safe. Shell plans to deploy predictive maintenance applications — and already applies machine learning to improve the accuracy and consistency of a horizontal well’s directional control to reach the most productive layers of rock containing oil and gas.

Bühler, a Swiss grain sorting tech firm, is partnering with Microsoft to use cloud and AI technologies to increase food safety and reduce waste.

Microsoft is helping H&M reimagine the customer experience and launch new brands through intelligent tech. One example is the “Magic Mirror” at its flagship store in Times Square, which uses Microsoft AI tech to identify people that pause in front of the mirror and then offers potential shoppers selfies, style advice and discounts at the store.

What Are the Most Common Issues You See Preventing Companies from Realizing the Benefits of AI?

What we’ve learned from talking with our own customers is that many of them aren’t sure where to start when it comes to incorporating AI. There are three main things that are holding them back: having the right skills and AI capabilities, how to implement AI on both their existing data and external data sources and concerns about privacy, reliability, and scale.

When implementing AI, organizations must first identify the right business opportunity for AI. Do they want to enhance customer service, improve productivity, reduce manufacturing defects, or something entirely unique? AI scenarios are business-and industry-specific. Businesses looking to implement AI can consider building the following:

Systems of intelligence — Digital agents, ranging from simple bots to systems for customer care, all built on conversational AI. Organizations with lower AI maturity can implement chatbots to deliver better services and raise their AI maturity without hiring data scientists.

Patterns of object definition and detection — Using AI image recognition, for example, to spot defects on production lines and transform manufacturing processes, or to provide spatial occupancy intelligence for retailers to understand how shoppers move through a store.

AI-assisted professionals — Using machine reading and comprehension, for example, to help legal, HR or other workers keep up with growing volumes of information, with AI systems smart enough to flag potential issues in documents so the professionals can focus their attention, address risks, and get more done.

Where Do You Think the Biggest Opportunities Are in the Implementation of AI?

Over the next five years, business decision makers expect AI to have a positive impact on growth (90%), productivity (86%), innovation (84%) and job creation (69%) in their country and industry. In the public sector, it will help with citizen engagement (73%). In the private sector, AI will help them improve customer services (80%).

We’ve moved beyond the hype. Many describe AI as important to solving their organizations’ strategic challenges, with 57% saying that it is “somewhat” important and a further 37% characterizing it as “very” important.

There is a tremendous opportunity for AI to augment human abilities across industries while capitalizing on unique human capacities for creativity and agility — human characteristics that are difficult for computers to mimic. For example:

Manufacturing: AI will be used in research and development, predictive analysis and real-time operations management.

Healthcare: AI will help risk management and analytics, social engagement and information sharing.

What Are Your Biggest Concerns Regarding AI?

We are in the early stages of understanding what AI systems will be capable of. For now, AI systems are very good at doing certain tasks, like recognizing photos or words, but they can’t match even a baby’s ability to understand the world around her through a combination of senses such as touch, sight, hearing, and smell.

As AI systems get more sophisticated and start to play a larger role in people’s lives, it’s imperative for companies to develop and adopt clear principles that guide the people building, using and applying AI systems. Among other things, these principles should ensure that AI systems are fair, reliable and safe, private and secure, inclusive, transparent and accountable. To help achieve this, the people designing AI systems should reflect the diversity of the world in which we live.

The advances we are making in AI won’t happen at one company, or thanks to one computer scientist, and they won’t happen responsibly without a strong community working together. That’s why Microsoft is a co-founder of the Partnership on AI, and it’s why our researchers regularly collaborate with academics and experts at other research institutions. It’s also why Microsoft has forged industry partnerships with both Amazon and Facebook to make AI more accessible to everyone.

We are optimistic about the future of AI, and we think AI advances will solve many more challenges than they present. Our approach to AI is grounded in, and consistent with, our company mission to help every person and organization on the planet to achieve more.